Fleet Management and Logistics

TEODOR GABRIEL CRAINIC, DIRECTOR The Centre for Research on Transportation (C.R.T.) was founded in 1971 by the Universite de Montreal. From 1988 on, it is jointly managed by the Universite de Montreal and its affiliated schools, the Ecole des Hautes Etudes Commerciales and Ecole Poly technique. Professors, students and researchers from many institutions in the Montreal area join forces at the C.R.T. to analyze transportation, logistics and telecommunication systems from a multidisciplinary perspective. The C.R.T. pursues three major, complementary objectives: training of high-level specialists; the advancement of knowledge and technology; the transfer of technology towards industry and the public sector. Its main field of expertise is the develop ment of quantitative and computer-based models and methods for the analysis of urban, regional and intercity transportation networks, as well as telecommunication systems. This applies to the study of passenger and commodity flows, as well as to the socioeconomic aspects of transportation: policy, regulation, economics. The twenty-fifth anniversary of the C.R.T. offered the opportunity to evaluate past accomplishments and to identify future trends and challenges. Five colloquia were thus organized on major research and application themes that also reflected our main research areas. They gathered together internationally renowned researchers who linked recent scientific and technological advances to modeling and methodological challenges waiting to be tackled, particularly concerning new problems and applica tions, and the increasingly widespread use of new technologies.

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The variety and complexity of the transportation field is reflected by the richness of research areas, models, methods, and software. The ten chapters of emFleet Management and Logistics/em describe some of the most recent operations-research advances in the field of transportation and logistics. br/ The first four chapters deal with various versions of the Vehicle Routing Problem (VRP), probably the most central model in distribution management. The fourth chapter discusses the Inventory Routing Problem, a variant of the VRP that combines routing and customer resupplying decisions. Growing competition in the area of logistics has forced several firms to pay closer attention to customer service and timeliness of deliveries. Dynamic real-time vehicle routing and dispatching is central to several fast-growing sectors such as emergency services, repairman dispatching, express courier delivery, and dial-a-ride transportation, as well as truckload and container operations. These fleet management issues are discussed in Chapters Five, Six and Seven. Chapters Eight and Nine address the crew scheduling problem faced by all airlines, combined locations-routing problems, and simultaneous routing decisions. In the final chapter the authors review the area of parallel metaheuristics, and provide new insight by studying commonalities among parallel implementations across several types of metaheuristics.

Contenu
1 Exact Solution of the Vehicle Routing Problem.- 1.1 Introduction.- 1.2 Problem Definition and Notation.- 1.3 Basic Reduction Rules.- 1.4 The Asymmetric CVRP.- 1.5 Branch-and-Bound Algorithms for the Symmetric CVRP.- 1.6 Branch-and-Cut Algorithms for the Symmetric CVRP.- 1.7 The Set Partitioning Approach.- 1.8 Conclusions.- References.- 2 Metaheuristics in Vehicle Routing.- 2.1 Introduction.- 2.2 Overview of Three Metaheuristics.- 2.3 Computational Experience.- 2.4 Large-Scale Vehicle Routing Problems.- 2.5 Future Directions in Vehicle Routing Research.- References.- 3 A Unified Framework for Deterministic Time Constrained Vehicle Routing and Crew Scheduling Problems.- 3.1 Introduction.- 3.2 Relations between Time Constrained Problems.- 3.3 A Unified Formulation.- 3.4 Solution Methodology.- 3.5 Conclusion.- References.- 4 The Inventory Routing Problem.- 4.1 Introduction.- 4.2 The Inventory Routing Problem.- 4.3 The Single Customer Problem.- 4.4 The Two-Customer Problem.- 4.5 Solution Approaches.- 4.6 Solution Approaches under Investigation.- 4.7 Practical Issues.- 4.8 Test Problems.- References.- 5 Dynamic Vehicle Routing and Dispatching.- 5.1 Introduction.- 5.2 Dial-a-Ride Problems.- 5.3 Repair and Courier Services.- 5.4 Express Mail Delivery.- 5.5 Concluding Remarks.- References.- 6 On Languages for Dynamic Resource Scheduling Problems.- 6.1 Introduction.- 6.2 The Language of Applications.- 6.3 A Representation Language.- 6.4 A Mathematical Language.- 6.5 A Software Language.- 6.6 A Modeling Process.- References.- 7 Solving Stochastic Routing Problems.- 7.1 Introduction.- 7.2 Formulation.- 7.3 The Integer L-Shaped Method.- 7.4 Implementation and Results.- 7.5 Conclusion.- References.- 8 Crew Scheduling in Air Transportation.- 8.1 Introduction.- 8.2 A Variety of CrewScheduling Problems.- 8.3 A Unified Formulation for Air Crew Scheduling Problems.- 8.4 Solution Methodology.- 8.5 Computational Results.- 8.6 Conclusion.- References.- 9 Path, Tree and Cycle Location.- 9.1 Introduction.- 9.2 Notations and Formulations.- 9.3 Paths with Fixed End Points (Po-d).- 9.4 Paths without Fixed End Points (P).- 9.5 Trees.- 9.6 Cycles with an Origin (Co).- 9.7 Cycles without a Fixed Origin (C).- 9.8 Conclusion.- References.- 10 Parallel Metaheuristics.- 10.1 Introduction.- 10.2 Parallel Metaheuristics.- 10.3 Type 1: Low-Level Parallelization.- 10.4 Type 2: Parallelization by Domain Decomposition.- 10.5 Type 3: Multiple Search Strategies.- 10.6 Conclusions and Perspectives.- References.